Fast enhancement algorithm of highway tunnel image based on constraint of imaging model. Issue 10 (1st October 2018)

• Record Type: Journal Article
• Authors: Yongxue, Li; Min, Zhao; Dihua, Sun
• Is Part Of: IET image processing. Volume 12:Issue 10(2018)
• Page Start: 1730
• Page End: 1735
• Publication Date: 2018-10-01
• Subjects: image enhancement -- tunnels -- roads; partitioned atmospheric light -- imaging model constraint -- monitored image blurring -- dim environment -- tunnel image illumination -- imaging model constraints -- local atmospheric light -- global atmospheric light -- fast image enhancement algorithm -- highway tunnel image; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2017.0902
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : Due to uneven illumination and dim environment in the tunnel, the monitored image is blurred, which makes it difficult to recognise the traffic status. Therefore, it is necessary to enhance the tunnel image in advance. In this study, a fast image enhancement algorithm based on imaging model constraint is proposed. First, the method uses the combination of global atmospheric light and partitioned atmospheric light to estimate the local atmospheric light. Second, the transmission is estimated based on the formula derived from the imaging model constraints. Third, the method uses a constant instead of illumination to balance tunnel image illumination. Last, the tunnel image is enhanced according to the imaging model. Experimental and comparative analysis results show that the proposed method can rapidly and effectively enhance the tunnel image.